Self-Reported and Physiologic Reactions to Third BNT162b2 mRNA COVID-19 (Booster) Vaccine Dose

Despite extensive technological advances in recent years, objective and continuous assessment of physiologic measures after vaccination is rarely performed. We conducted a prospective observational study to evaluate short-term self-reported and physiologic reactions to the booster BNT162b2 mRNA (Pfizer-BioNTech, https://www.pfizer.com) vaccine dose. A total of 1,609 participants were equipped with smartwatches and completed daily questionnaires through a dedicated mobile application. The extent of systemic reactions reported after the booster dose was similar to that of the second dose and considerably greater than that of the first dose. Analyses of objective heart rate and heart rate variability measures recorded by smartwatches further supported this finding. Subjective and objective reactions after the booster dose were more apparent in younger participants and in participants who did not have underlying medical conditions. Our findings further support the safety of the booster dose from subjective and objective perspectives and underscore the need for integrating wearables in clinical trials.

daily questionnaire and to report their vaccine date and specific hour. In this study, we will consider for each participant, the 7-days period before any vaccination dose as the baseline period.

Participants
The inclusion criteria for the PerMed study includes those aged >18 years.
Persons who are not eligible to give and sign a consent form of their free are excluded. In this study, we will analyze the data of participants aged 18 years and above, who reported receiving at least 1 dose of the BNT162b2 mRNA COVID-19 vaccine after joining the PerMed study. To recruit participants and ensure they complete all the study's requirements, we will hire a professional survey company. Potential participants will be recruited through advertisements in social media, online banners, and word-of-mouth.
The survey company is responsible for guaranteeing the participants meet the study's requirements, in particular, that the questionnaires are filled daily, ensuring the smartwatches are charged constantly and worn properly, and assisting participants resolve technical problems.

Study Procedures
Before participation in the study, all participants will be advised orally and in writing about the nature of the experiments and give written, informed consent. At this time, participants will be asked to complete an enrollment questionnaire that includes demographic information and health status. In addition, participants will be asked to install 2 applications on their mobile phones: an application that passively collects data from the smartwatch and the PerMed application, which enables participants to fill in the daily questionnaires. Participants will be given instructions regarding the self-reported symptoms questionnaires and how to operate the smartwatch, which they will wear as much as they can.

Enrollment Questionnaire
All participants will fill a 1-time enrollment questionnaire that includes demographic questions and questions about the participant's health condition in general.
Specifically, the questionnaire will include the following: age, sex, height, weight and underlying medical conditions (Listed in Table 1, main text). Other questions such as name, address, phone and email will be recorded and used by the survey company to contact the participants. The answers will be filled-in directly by the survey company to the study's secured dashboard.

Monitoring Device
Participants will be equipped with Garmin Vivosmart 4 smart fitness trackers.
Among other features, the smartwatch provides all-day heart rate and heart rate variability and during-night blood oxygen saturation level tracking capabilities (25).
The optical wrist heart rate (HR) monitor of the smartwatch is designed to continuously monitor a user's heart rate. The frequency at which heart rate is measured varies and may depend on the level of activity of the user: when the user starts an activity, the optical HR monitor's measurement frequency increases.
Since heart rate variability (HRV) is not easily accessible through Garmin's application programming interface (API), we use Garmin's stress level instead, which is calculated based on HRV. Specifically, the device uses heart rate data to determine the interval between each heartbeat. The variable length of time between each heartbeat is regulated by the body's autonomic nervous system. Less variability between beats correlates with higher stress levels, whereas an increase in variability indicates less stress (26). A similar relationship between HRV and stress was also seen in (27,28).
The Pulse Ox monitor of the smartwatch uses a combination of red and infrared lights with sensors on the back of the device to estimate the percentage of oxygenated blood (peripheral oxygen saturation). The Pulse Ox monitor is activated each day at a fixed time for a period of 4 hours (the default is 2:00 AM-6:00 AM).
Examining the data collected in our study, we identified an HR sample roughly every 15 seconds, an HRV sample every 180 seconds, and an blood oxygen saturation level sample every 60 seconds.
While the Garmin smartwatch provides state-of-the-art wrist monitoring, it is not a medical-grade device, and some readings may be inaccurate under certain circumstances, depending on factors such as the fit of the device and the type and intensity of the activity undertaken by a participant (29)(30)(31).

Vaccination Questionnaire
The vaccination questionnaire we will use includes the following question: COVID-19 vaccination -date, time, and dose number.

Daily Questionnaires
All participants will complete the daily self-reported questionnaire in a dedicated application (the PerMed mobile application). The daily questionnaire we will use includes the following questions:

Data Storage
Data collected from the mobile phone application and from the smartwatches will be stored on a secure server within Tel Aviv University facilities. The server runs a CentOS operating system and is located in Software Engineering Building at Tel Aviv University. This server is protected behind the university's firewall and is not connected to external networks. In addition, a secure connection through an SSL protocol and a trusted certificate will be obtained for the transfer of information from the mobile phone application into the secured server.
Access will be restricted to investigators in the study. The information from the mobile application will be stored in a structured manner on the secured server without any explicitly identifying information (name, ID number, email). Each participant will be assigned a coded participant number that will be used to identify the subject in the database. The code with the identified information will be stored in an encrypted form on a separate secured server that only the research manager will have access to. Access to all servers is restricted with username and password.
All (non-digital) questionnaires and signed informed consent documents will be stored in a secured cabinet in Tel Aviv University, to which only the research manager and the principal investigators will have access. No data collected as part of the study will be added to persons' medical charts.

Data Processing
We will perform several preprocessing steps. Concerning the daily questionnaires, in cases where participants will fill in the daily questionnaire more than once on a given day, only the last entry for that day will be considered, as it is reasoned that the last one likely best represented the entire day. Self-reported symptoms that are entered as the free text will be manually categorized. With regard to the smartwatch physiologic indicators, data will first be aggregated per hour (by taking the mean value). Then, to impute missing values, we will perform a linear interpolation. Finally, data will be smoothed by calculating the moving average value using a 5-hour sliding window.

Data Analysis
For each participant, we defined the 7-day period before vaccination as a baseline.
First, for the period of 48 hours from vaccination, we will calculate the percentage of participants who reported new local or systemic reactions compared with their baseline period (i.e., the last questionnaire each participant filled during the baseline period). For each reaction, a 90% confidence interval will be calculated, assuming a β distribution, with parameter corresponding to the number of participants reporting that reaction plus one (i.e., "successes"), and parameter corresponding to the number of participants who did not report that reaction plus one (i.e., "failures"). To determine the statistical significance of differences between the first and third doses and between the second and third doses as reflected by the extent of reported reactions, we will use a 2-proportion Ztest.
Next, we will calculate the changes in well-being indicators reported postvaccination compared with those reported during the baseline period. Specifically, for each indicator and each participant, we will calculate the difference between the value in each of the 3 days post-vaccination and the corresponding value in the baseline period (i.e., the last questionnaire filled during the baseline period). Then, for each indicator and each of the 3 days post vaccination, we will calculate the mean difference value over all participants and the associated 90% confidence interval.
Finally, we will compare the changes in smartwatch physiologic indicators over the 7 days (168 hours) post vaccination with those of the baseline period. To do so, we will perform the following steps. First, for each participant and each hour during the 7 days post vaccination, we will calculate the difference between that hour's indicator value and that of the corresponding hour in the baseline period (keeping the same day of the week and same hour during the day). Then, we will calculate the mean difference value for each hour over all participants, as well as the 90% confidence interval, corresponding to a significance level of 0.05 in a 1-sided t-test. To determine the statistical significance of differences between the first and third doses and between the second and third doses as reflected by changes in smartwatch indicators during the 48 hours post-vaccination, we will use a 2-sample t-test with unequal variance.

Potential Risks and Risk Management
No specific risks arising from the smartwatches are expected, as the device is already commercialized with no known adverse reactions. The main risk in this study is the leakage of private data which we intend to manage as we describe in the following section.

Privacy/Confidentiality
Results from this study will be handled at an aggregated level. Individual data records will remain confidential and will not be published or shared with any third party.
report forms) will be stored in locked cabinets during the study and following its completion. A file containing the personal details of the participants will be coded to help preserve confidentiality and will be separated from all other data collected throughout the study. This file will be kept by the principal investigator. Data will be stored on computers in password-protected files.
The data obtained from the smartwatch used in this study will be linked to a coded participant number. The smartwatch does not include a global positioning system. Data collected by the PerMed application will arrive directly to PerMed back-end servers and will be stored securely.

Changes in Objective Physiologic Indicators Measured through the Smartwatch following the Three Vaccine Doses
Changes in objective physiologic indicators observed during the first 2 days after the second and third vaccine doses are similar, and considerably greater than those observed following the first dose.
Appendix Figure 1. Changes in objective physiologic indicators measured through the smartwatch during the first 2 days after vaccine. Mean difference in smartwatch-recorded heart rate and heart rate variability-based following the first, second and third dose, compared with their baseline levels. Changes in objective physiologic indicators were calculated by subtracting the baseline values from the mean value of the first 2 days following the vaccine dose. Error bars represent 90% confidence intervals.

Changes in reported well-being indicators -stratification by age group
Changes in well-being observed during the first 2 days after the third vaccine dose were found to be higher for participants younger than 50 years compared with those between 50 and 65 years, and consequently higher than those older than 65 years, with the exception of reported stress level (Appendix Figure 2).

Changes in Physiologic Indicators -Stratification by Sex
Changes in physiologic indicators after the third vaccine dose stratified by sex were consistent with those observed in the general population (considerable changes during the first 2 days after vaccine administration that faded nearly entirely after 3 days).
These changes were found to be higher for females compared with males (Appendix Figure 6).

Pairwise Analysis of Doses
A considerable number of participants joined our study after receiving the first or second dose. Thus, in our main analyses, we compared the third dose to the first or second dose by using statistical significance tests for comparing the means of 2 partially overlapping samples with unequal variance. To further support the results of our main analyses, we also conducted an analysis where we examined changes in reactions for the subgroups of participants who reported receiving all 3 doses. To determine the statistical significance of differences in the proportions of participants' self-reported reactions between doses, we used McNemar tests (Appendix Table 1). To determine the statistical significance of differences in the change in smartwatch measurements between doses we used paired t-tests (Appendix Table 2).

Calculation of Required Sample Size
The primary goal of the study was to compare reactions following the third dose to those observed in the first and second doses. Particularly, we wanted to know whether reactions following the third dose will be greater than those observed following the second dose. The logic for this notion is the expectation that reactions following primary exposure are typically milder than those following subsequent exposure (namely second or booster dose). Thus, to determine the required sample size, we first identified the five most prevalent systemic reactions observed during the Pfizer clinical trial: headache, fatigue, fever, chills, and muscle pain. Based on those trials, the frequency of these reactions ranged between 16%-59% in persons 16-55, and 11%-51% in persons >55 (7). more prevalent at least 10% than those observed in the clinical trials. We conservatively assumed a non-repeated framework (i.e., different participants received the third dose than those who received the first and second doses). Taken together, we used a Z-test to evaluate the difference in the two population proportions. Under the standard assumptions of = 0.05 , = 1 − = 0.8, and the formula (Z α+ Zβ) 2 × (p1(1 -p1) + p2(1 -p2))/(p1 -p2) 2 , we derived a required n = 203-282 in persons 18-55 (which correspond to 16%-59%) namely >282, and 164-302 (which corresponds to 11%-51%) namely n > 302 in persons >55. To conclude, the actual number of participants in our study is considerably larger than the one required to ensure statistical significance.
The primary goal of the study was to compare reactions following the third dose to those